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Rutowicz K, Lüthi J, de Groot R, Holtackers R, Yakimovich Y, Pazmiño DM, Gandrillon O, Pelkmans L, Baroux C. Multiscale chromatin dynamics and high entropy in plant iPSC ancestors. J Cell Sci 2024; 137:jcs261703. [PMID: 38738286 PMCID: PMC11234377 DOI: 10.1242/jcs.261703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 04/29/2024] [Indexed: 05/14/2024] Open
Abstract
Plant protoplasts provide starting material for of inducing pluripotent cell masses that are competent for tissue regeneration in vitro, analogous to animal induced pluripotent stem cells (iPSCs). Dedifferentiation is associated with large-scale chromatin reorganisation and massive transcriptome reprogramming, characterised by stochastic gene expression. How this cellular variability reflects on chromatin organisation in individual cells and what factors influence chromatin transitions during culturing are largely unknown. Here, we used high-throughput imaging and a custom supervised image analysis protocol extracting over 100 chromatin features of cultured protoplasts. The analysis revealed rapid, multiscale dynamics of chromatin patterns with a trajectory that strongly depended on nutrient availability. Decreased abundance in H1 (linker histones) is hallmark of chromatin transitions. We measured a high heterogeneity of chromatin patterns indicating intrinsic entropy as a hallmark of the initial cultures. We further measured an entropy decline over time, and an antagonistic influence by external and intrinsic factors, such as phytohormones and epigenetic modifiers, respectively. Collectively, our study benchmarks an approach to understand the variability and evolution of chromatin patterns underlying plant cell reprogramming in vitro.
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Affiliation(s)
- Kinga Rutowicz
- Plant Developmental Genetics, Institute of Plant and Microbial Biology, University of Zurich, 8008 Zurich, Switzerland
| | - Joel Lüthi
- Department of Molecular Life Sciences, University of Zurich, 8050 Zurich, Switzerland
| | - Reinoud de Groot
- Department of Molecular Life Sciences, University of Zurich, 8050 Zurich, Switzerland
| | - René Holtackers
- Department of Molecular Life Sciences, University of Zurich, 8050 Zurich, Switzerland
| | - Yauhen Yakimovich
- Department of Molecular Life Sciences, University of Zurich, 8050 Zurich, Switzerland
| | - Diana M. Pazmiño
- Plant Developmental Genetics, Institute of Plant and Microbial Biology, University of Zurich, 8008 Zurich, Switzerland
| | - Olivier Gandrillon
- Laboratory of Biology and Modeling of the Cell, University of Lyon, ENS de Lyon,69342 Lyon, France
| | - Lucas Pelkmans
- Department of Molecular Life Sciences, University of Zurich, 8050 Zurich, Switzerland
| | - Célia Baroux
- Plant Developmental Genetics, Institute of Plant and Microbial Biology, University of Zurich, 8008 Zurich, Switzerland
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Ediriwickrema A, Nakauchi Y, Fan AC, Köhnke T, Hu X, Luca BA, Kim Y, Ramakrishnan S, Nakamoto M, Karigane D, Linde MH, Azizi A, Newman AM, Gentles AJ, Majeti R. A single cell framework identifies functionally and molecularly distinct multipotent progenitors in adult human hematopoiesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.07.592983. [PMID: 38766031 PMCID: PMC11100686 DOI: 10.1101/2024.05.07.592983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Hematopoietic multipotent progenitors (MPPs) regulate blood cell production to appropriately meet the biological demands of the human body. Human MPPs remain ill-defined whereas mouse MPPs have been well characterized with distinct immunophenotypes and lineage potencies. Using multiomic single cell analyses and complementary functional assays, we identified new human MPPs and oligopotent progenitor populations within Lin-CD34+CD38dim/lo adult bone marrow with distinct biomolecular and functional properties. These populations were prospectively isolated based on expression of CD69, CLL1, and CD2 in addition to classical markers like CD90 and CD45RA. We show that within the canonical Lin-CD34+CD38dim/loCD90CD45RA-MPP population, there is a CD69+ MPP with long-term engraftment and multilineage differentiation potential, a CLL1+ myeloid-biased MPP, and a CLL1-CD69-erythroid-biased MPP. We also show that the canonical Lin-CD34+CD38dim/loCD90-CD45RA+ LMPP population can be separated into a CD2+ LMPP with lymphoid and myeloid potential, a CD2-LMPP with high lymphoid potential, and a CLL1+ GMP with minimal lymphoid potential. We used these new HSPC profiles to study human and mouse bone marrow cells and observe limited cell type specific homology between humans and mice and cell type specific changes associated with aging. By identifying and functionally characterizing new adult MPP sub-populations, we provide an updated reference and framework for future studies in human hematopoiesis.
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3
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Dussiau C, Comont T, Knosp C, Vergnolle I, Bravetti C, Canali A, Houvert A, Largeaud L, Daveaux C, Zaroili L, Friedrich C, Boussaid I, Zalmai L, Almire C, Rauzy O, Willems L, Birsen R, Bouscary D, Fontenay M, Kosmider O, Chapuis N, Vergez F. Loss of hematopoietic progenitors heterogeneity is an adverse prognostic factor in lower-risk myelodysplastic neoplasms. Leukemia 2024; 38:1131-1142. [PMID: 38575672 DOI: 10.1038/s41375-024-02234-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 03/15/2024] [Accepted: 03/19/2024] [Indexed: 04/06/2024]
Abstract
Myelodysplastic neoplasms (MDS) are characterized by clonal evolution starting from the compartment of hematopoietic stem and progenitors cells (HSPCs), leading in some cases to leukemic transformation. We hypothesized that deciphering the diversity of the HSPCs compartment may allow for the early detection of an emergent sub-clone that drives disease progression. Deep analysis of HSPCs repartition by multiparametric flow cytometry revealed a strong disorder of the hematopoietic branching system in most patients at diagnosis with different phenotypic signatures closely related to specific MDS features. In two independent cohorts of 131 and 584 MDS, the HSPCs heterogeneity quantified through entropy calculation was decreased in 47% and 46% of cases, reflecting a more advanced state of the disease with deeper cytopenias, higher IPSS-R risk and accumulation of somatic mutations. We demonstrated that patients with lower-risk MDS and low CD34 + CD38+HSPCs entropy had an adverse outcome and that this parameter is as an independent predictive biomarker for progression free survival, leukemia free survival and overall survival. Analysis of HSPCs repartition at diagnosis represents therefore a very powerful tool to identify lower-risk MDS patients with a worse outcome and valuable for clinical decision-making, which could be fully integrated in the MDS diagnostic workflow.
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Affiliation(s)
- Charles Dussiau
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Thibault Comont
- Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Service de Médecine Interne, Toulouse, France
- Université Toulouse III Paul Sabatier, Toulouse, France
- Cancer Research Center of Toulouse, UMR1037-INSERM, ERL5294 CNRS, Toulouse, France
| | - Camille Knosp
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Inès Vergnolle
- Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France
| | - Clotilde Bravetti
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Alban Canali
- Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France
| | - Amandine Houvert
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Laetitia Largeaud
- Université Toulouse III Paul Sabatier, Toulouse, France
- Cancer Research Center of Toulouse, UMR1037-INSERM, ERL5294 CNRS, Toulouse, France
- Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France
| | - Christian Daveaux
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Laila Zaroili
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Chloé Friedrich
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Ismaël Boussaid
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Loria Zalmai
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France
| | - Carole Almire
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France
| | - Odile Rauzy
- Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Service de Médecine Interne, Toulouse, France
- Université Toulouse III Paul Sabatier, Toulouse, France
- Cancer Research Center of Toulouse, UMR1037-INSERM, ERL5294 CNRS, Toulouse, France
| | - Lise Willems
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie clinique, Hôpital Cochin, Paris, France
| | - Rudy Birsen
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie clinique, Hôpital Cochin, Paris, France
| | - Didier Bouscary
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie clinique, Hôpital Cochin, Paris, France
| | - Michaela Fontenay
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Olivier Kosmider
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France
| | - Nicolas Chapuis
- Assistance Publique-Hôpitaux de Paris. Centre-Université Paris Cité, Service d'hématologie biologique, Hôpital Cochin, Paris, France.
- Université Paris Cité, Institut Cochin, CNRSUMR8104, INSERM U1016, Paris, France.
| | - François Vergez
- Université Toulouse III Paul Sabatier, Toulouse, France
- Cancer Research Center of Toulouse, UMR1037-INSERM, ERL5294 CNRS, Toulouse, France
- Centre Hospitalier Universitaire de Toulouse, Institut Universitaire du Cancer de Toulouse Oncopole, Laboratoire d'Hématologie, Toulouse, France
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Fourneaux C, Racine L, Koering C, Dussurgey S, Vallin E, Moussy A, Parmentier R, Brunard F, Stockholm D, Modolo L, Picard F, Gandrillon O, Paldi A, Gonin-Giraud S. Differentiation is accompanied by a progressive loss in transcriptional memory. BMC Biol 2024; 22:58. [PMID: 38468285 DOI: 10.1186/s12915-024-01846-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 02/13/2024] [Indexed: 03/13/2024] Open
Abstract
BACKGROUND Cell differentiation requires the integration of two opposite processes, a stabilizing cellular memory, especially at the transcriptional scale, and a burst of gene expression variability which follows the differentiation induction. Therefore, the actual capacity of a cell to undergo phenotypic change during a differentiation process relies upon a modification in this balance which favors change-inducing gene expression variability. However, there are no experimental data providing insight on how fast the transcriptomes of identical cells would diverge on the scale of the very first two cell divisions during the differentiation process. RESULTS In order to quantitatively address this question, we developed different experimental methods to recover the transcriptomes of related cells, after one and two divisions, while preserving the information about their lineage at the scale of a single cell division. We analyzed the transcriptomes of related cells from two differentiation biological systems (human CD34+ cells and T2EC chicken primary erythrocytic progenitors) using two different single-cell transcriptomics technologies (scRT-qPCR and scRNA-seq). CONCLUSIONS We identified that the gene transcription profiles of differentiating sister cells are more similar to each other than to those of non-related cells of the same type, sharing the same environment and undergoing similar biological processes. More importantly, we observed greater discrepancies between differentiating sister cells than between self-renewing sister cells. Furthermore, a progressive increase in this divergence from first generation to second generation was observed when comparing differentiating cousin cells to self renewing cousin cells. Our results are in favor of a gradual erasure of transcriptional memory during the differentiation process.
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Affiliation(s)
- Camille Fourneaux
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Laëtitia Racine
- Ecole Pratique des Hautes Etudes, PSL Research University, Sorbonne Université, INSERM, CRSA, Paris, 75012, France
| | - Catherine Koering
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Sébastien Dussurgey
- Plateforme AniRA-Cytométrie, Université Claude Bernard Lyon 1, CNRS UAR3444, Inserm US8, ENS de Lyon, SFR Biosciences, Lyon, F-69007, France
| | - Elodie Vallin
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Alice Moussy
- Ecole Pratique des Hautes Etudes, PSL Research University, Sorbonne Université, INSERM, CRSA, Paris, 75012, France
| | - Romuald Parmentier
- Ecole Pratique des Hautes Etudes, PSL Research University, Sorbonne Université, INSERM, CRSA, Paris, 75012, France
| | - Fanny Brunard
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Daniel Stockholm
- Ecole Pratique des Hautes Etudes, PSL Research University, Sorbonne Université, INSERM, CRSA, Paris, 75012, France
| | - Laurent Modolo
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Franck Picard
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Olivier Gandrillon
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Inria Center, Grenoble Rhone-Alpes, Equipe Dracula, Villeurbanne, F69100, France
| | - Andras Paldi
- Ecole Pratique des Hautes Etudes, PSL Research University, Sorbonne Université, INSERM, CRSA, Paris, 75012, France
| | - Sandrine Gonin-Giraud
- Laboratoire de Biologie et Modélisation de la Cellule, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France.
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5
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Vink CS, Popravko A, Dzierzak E. De novo hematopoietic (stem) cell generation - A differentiation or stochastic process? Curr Opin Cell Biol 2023; 85:102255. [PMID: 37806296 DOI: 10.1016/j.ceb.2023.102255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 08/28/2023] [Accepted: 09/10/2023] [Indexed: 10/10/2023]
Abstract
The hematopoietic system is one of the earliest tissues to develop. De novo generation of hematopoietic progenitor and stem cells occurs through a transdifferentiation of (hemogenic) endothelial cells to hematopoietic identity, resulting in the formation of intra-aortic hematopoietic cluster (IAHC) cells. Heterogeneity of IAHC cell phenotypes and functions has stymied the field in its search for the transcriptional program of emerging hematopoietic stem cells (HSCs), given that an individual IAHC cannot be simultaneously examined for function and transcriptome. Several models could account for this heterogeneity, including a novel model suggesting that the transcriptomes of individual emerging IAHC cells are in an unstable/metastable state, with pivotal hematopoietic transcription factors expressed dynamically due to transcriptional pulsing and combinatorial activities. The question remains - how is functional hematopoietic cell fate established - is the process stochastic? This article touches upon these important issues, which may be relevant to the field's inability to make HSCs ex vivo.
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Affiliation(s)
- Chris S Vink
- The University of Edinburgh, Centre for Inflammation Research, Edinburgh, Midlothian, Scotland, EH16 4UU, UK
| | - Anna Popravko
- The University of Edinburgh, Centre for Inflammation Research, Edinburgh, Midlothian, Scotland, EH16 4UU, UK
| | - Elaine Dzierzak
- The University of Edinburgh, Centre for Inflammation Research, Edinburgh, Midlothian, Scotland, EH16 4UU, UK.
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Aslan Kamil M, Fourneaux C, Yilmaz A, Stavros S, Parmentier R, Paldi A, Gonin-Giraud S, deMello AJ, Gandrillon O. An image-guided microfluidic system for single-cell lineage tracking. PLoS One 2023; 18:e0288655. [PMID: 37527253 PMCID: PMC10393162 DOI: 10.1371/journal.pone.0288655] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 06/30/2023] [Indexed: 08/03/2023] Open
Abstract
Cell lineage tracking is a long-standing and unresolved problem in biology. Microfluidic technologies have the potential to address this problem, by virtue of their ability to manipulate and process single-cells in a rapid, controllable and efficient manner. Indeed, when coupled with traditional imaging approaches, microfluidic systems allow the experimentalist to follow single-cell divisions over time. Herein, we present a valve-based microfluidic system able to probe the decision-making processes of single-cells, by tracking their lineage over multiple generations. The system operates by trapping single-cells within growth chambers, allowing the trapped cells to grow and divide, isolating sister cells after a user-defined number of divisions and finally extracting them for downstream transcriptome analysis. The platform incorporates multiple cell manipulation operations, image processing-based automation for cell loading and growth monitoring, reagent addition and device washing. To demonstrate the efficacy of the microfluidic workflow, 6C2 (chicken erythroleukemia) and T2EC (primary chicken erythrocytic progenitors) cells are tracked inside the microfluidic device over two generations, with a cell viability rate in excess of 90%. Sister cells are successfully isolated after division and extracted within a 500 nL volume, which was demonstrated to be compatible with downstream single-cell RNA sequencing analysis.
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Affiliation(s)
- Mahmut Aslan Kamil
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Camille Fourneaux
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard, Lyon, France
| | | | - Stavrakis Stavros
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Romuald Parmentier
- Ecole Pratique des Hautes Etudes, St-Antoine Research Center, Inserm U938, PSL Research University, Paris, France
| | - Andras Paldi
- Ecole Pratique des Hautes Etudes, St-Antoine Research Center, Inserm U938, PSL Research University, Paris, France
| | - Sandrine Gonin-Giraud
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard, Lyon, France
| | - Andrew J deMello
- Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Zürich, Switzerland
| | - Olivier Gandrillon
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard, Lyon, France
- Inria, France
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7
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Toh K, Saunders D, Verd B, Steventon B. Zebrafish neuromesodermal progenitors undergo a critical state transition in vivo. iScience 2022; 25:105216. [PMID: 36274939 PMCID: PMC9579027 DOI: 10.1016/j.isci.2022.105216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 08/05/2022] [Accepted: 09/22/2022] [Indexed: 11/30/2022] Open
Abstract
The transition state model of cell differentiation proposes that a transient window of gene expression stochasticity precedes entry into a differentiated state. Here, we assess this theoretical model in zebrafish neuromesodermal progenitors (NMps) in vivo during late somitogenesis stages. We observed an increase in gene expression variability at the 24 somite stage (24ss) before their differentiation into spinal cord and paraxial mesoderm. Analysis of a published 18ss scRNA-seq dataset showed that the NMp population is noisier than its derivatives. By building in silico composite gene expression maps from image data, we assigned an 'NM index' to in silico NMps based on the expression of neural and mesodermal markers and demonstrated that cell population heterogeneity peaked at 24ss. Further examination revealed cells with gene expression profiles incongruent with their prospective fate. Taken together, our work supports the transition state model within an endogenous cell fate decision making event.
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Affiliation(s)
- Kane Toh
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK
| | - Dillan Saunders
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK
| | - Berta Verd
- Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK
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8
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Zreika S, Fourneaux C, Vallin E, Modolo L, Seraphin R, Moussy A, Ventre E, Bouvier M, Ozier-Lafontaine A, Bonnaffoux A, Picard F, Gandrillon O, Gonin-Giraud S. Evidence for close molecular proximity between reverting and undifferentiated cells. BMC Biol 2022; 20:155. [PMID: 35794592 PMCID: PMC9258043 DOI: 10.1186/s12915-022-01363-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 06/27/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND According to Waddington's epigenetic landscape concept, the differentiation process can be illustrated by a cell akin to a ball rolling down from the top of a hill (proliferation state) and crossing furrows before stopping in basins or "attractor states" to reach its stable differentiated state. However, it is now clear that some committed cells can retain a certain degree of plasticity and reacquire phenotypical characteristics of a more pluripotent cell state. In line with this dynamic model, we have previously shown that differentiating cells (chicken erythrocytic progenitors (T2EC)) retain for 24 h the ability to self-renew when transferred back in self-renewal conditions. Despite those intriguing and promising results, the underlying molecular state of those "reverting" cells remains unexplored. The aim of the present study was therefore to molecularly characterize the T2EC reversion process by combining advanced statistical tools to make the most of single-cell transcriptomic data. For this purpose, T2EC, initially maintained in a self-renewal medium (0H), were induced to differentiate for 24H (24H differentiating cells); then, a part of these cells was transferred back to the self-renewal medium (48H reverting cells) and the other part was maintained in the differentiation medium for another 24H (48H differentiating cells). For each time point, cell transcriptomes were generated using scRT-qPCR and scRNAseq. RESULTS Our results showed a strong overlap between 0H and 48H reverting cells when applying dimensional reduction. Moreover, the statistical comparison of cell distributions and differential expression analysis indicated no significant differences between these two cell groups. Interestingly, gene pattern distributions highlighted that, while 48H reverting cells have gene expression pattern more similar to 0H cells, they are not completely identical, which suggest that for some genes a longer delay may be required for the cells to fully recover. Finally, sparse PLS (sparse partial least square) analysis showed that only the expression of 3 genes discriminates 48H reverting and 0H cells. CONCLUSIONS Altogether, we show that reverting cells return to an earlier molecular state almost identical to undifferentiated cells and demonstrate a previously undocumented physiological and molecular plasticity during the differentiation process, which most likely results from the dynamic behavior of the underlying molecular network.
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Affiliation(s)
- Souad Zreika
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Azm Center for Research in Biotechnology and its Applications, LBA3B, EDST, Lebanese University, Tripoli, 1300, Lebanon
| | - Camille Fourneaux
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Elodie Vallin
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Laurent Modolo
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Rémi Seraphin
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Alice Moussy
- Ecole Pratique des Hautes Etudes, PSL Research University, UMRS951, INSERM, Univ-Evry, Paris, France
| | - Elias Ventre
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Inria Team Dracula, Inria Center Grenoble Rhone-Alpes, Grenoble, France
- Institut Camille Jordan, CNRS UMR 5208, Université Claude Bernard Lyon 1, Villeurbanne, France
| | - Matteo Bouvier
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Vidium solutions, Lyon, France
| | - Anthony Ozier-Lafontaine
- Nantes Université, Centrale Nantes, Laboratoire de mathématiques Jean Leray, LMJL, F-44000, Nantes, France
| | - Arnaud Bonnaffoux
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Vidium solutions, Lyon, France
| | - Franck Picard
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
| | - Olivier Gandrillon
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France
- Inria Team Dracula, Inria Center Grenoble Rhone-Alpes, Grenoble, France
| | - Sandrine Gonin-Giraud
- Laboratory of Biology and Modelling of the Cell, Université de Lyon, Ecole Normale Supérieure de Lyon, CNRS, UMR5239, Université Claude Bernard Lyon 1, Lyon, France.
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Senra D, Guisoni N, Diambra L. ORIGINS: a protein network-based approach to quantify cell pluripotency from scRNA-seq data. MethodsX 2022; 9:101778. [PMID: 35855951 PMCID: PMC9287638 DOI: 10.1016/j.mex.2022.101778] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 06/28/2022] [Indexed: 11/27/2022] Open
Abstract
Trajectory inference is a common application of scRNA-seq data. However, it is often necessary to previously determine the origin of the trajectories, the stem or progenitor cells. In this work, we propose a computational tool to quantify pluripotency from single cell transcriptomics data. This approach uses the protein-protein interaction (PPI) network associated with the differentiation process as a scaffold and the gene expression matrix to calculate a score that we call differentiation activity. This score reflects how active the differentiation network is in each cell. We benchmark the performance of our algorithm with two previously published tools, LandSCENT (Chen et al., 2019) and CytoTRACE (Gulati et al., 2020), for four healthy human data sets: breast, colon, hematopoietic and lung. We show that our algorithm is more efficient than LandSCENT and requires less RAM memory than the other programs. We also illustrate a complete workflow from the count matrix to trajectory inference using the breast data set.ORIGINS is a methodology to quantify pluripotency from scRNA-seq data implemented as a freely available R package. ORIGINS uses the protein-protein interaction network associated with differentiation and the data set expression matrix to calculate a score (differentiation activity) that quantifies pluripotency for each cell.
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10
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Mayer IM, Hoelbl-Kovacic A, Sexl V, Doma E. Isolation, Maintenance and Expansion of Adult Hematopoietic Stem/Progenitor Cells and Leukemic Stem Cells. Cancers (Basel) 2022; 14:1723. [PMID: 35406494 PMCID: PMC8996967 DOI: 10.3390/cancers14071723] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 03/23/2022] [Accepted: 03/25/2022] [Indexed: 12/12/2022] Open
Abstract
Hematopoietic stem cells (HSCs) are rare, self-renewing cells that perch on top of the hematopoietic tree. The HSCs ensure the constant supply of mature blood cells in a tightly regulated process producing peripheral blood cells. Intense efforts are ongoing to optimize HSC engraftment as therapeutic strategy to treat patients suffering from hematopoietic diseases. Preclinical research paves the way by developing methods to maintain, manipulate and expand HSCs ex vivo to understand their regulation and molecular make-up. The generation of a sufficient number of transplantable HSCs is the Holy Grail for clinical therapy. Leukemia stem cells (LSCs) are characterized by their acquired stem cell characteristics and are responsible for disease initiation, progression, and relapse. We summarize efforts, that have been undertaken to increase the number of long-term (LT)-HSCs and to prevent differentiation towards committed progenitors in ex vivo culture. We provide an overview and compare methods currently available to isolate, maintain and enrich HSC subsets, progenitors and LSCs and discuss their individual advantages and drawbacks.
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Affiliation(s)
| | | | - Veronika Sexl
- Institute of Pharmacology and Toxicology, University of Veterinary Medicine Vienna, 1210 Vienna, Austria; (I.M.M.); (A.H.-K.); (E.D.)
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